yapocis.lib.channels

Accomodate the differences between PIL, Numpy, and convenient programming models for OpenCL HWC <-> CHW ordering, conceptually.

Module Contents

Functions

histeq(im: yapocis.utils.typing.Array, nbr_bins: int = 2**16) → yapocis.utils.typing.Array	Histogram equalization of a 2D array
split_channels(rgb: yapocis.utils.typing.Array) → yapocis.utils.typing.Tuple[(Array, Array, Array)]	Split a 3xWxH array into WxH, WxH, WxH
join_channels(r: yapocis.utils.typing.Array, g: yapocis.utils.typing.Array, b: yapocis.utils.typing.Array) → yapocis.utils.typing.Array	Join WxH, WxH, WxH 2D arrays into a 3D Array with copied data

yapocis.lib.channels.histeq(im: yapocis.utils.typing.Array, nbr_bins: int = 2 ** 16) → yapocis.utils.typing.Array

Histogram equalization of a 2D array

Parameters

• im – 2D Array

• nbr_bins – number of bins

Returns

2d Array, dtype=np.float32

yapocis.lib.channels.split_channels(rgb: yapocis.utils.typing.Array) → yapocis.utils.typing.Tuple[Array, Array, Array]

Split a 3xWxH array into WxH, WxH, WxH

Parameters

rgb – 3D array

Returns

Tuple of 2D arrays that are copies of the original data

yapocis.lib.channels.join_channels(r: yapocis.utils.typing.Array, g: yapocis.utils.typing.Array, b: yapocis.utils.typing.Array) → yapocis.utils.typing.Array

Join WxH, WxH, WxH 2D arrays into a 3D Array with copied data

Parameters

• r – WxH array

• g – WxH array

• b – WxH array

Returns

3xWxH array